Quality measures of reconstruction filters for stereoscopic volume rendering

In direct volume rendering (DVR), the choice of reconstruction filter can have a significant effect on the visual appearance of the images produced and thus, on the perceived quality of a DVR rendered scene. This paper presents the results of a subjective experiment where participants stereoscopically viewed DVR rendered scenes and rated their subjective quality. The statistical analysis of the results focuses on the relationship between the quality of the stereoscopic scene and properties of the filters such as post-aliasing and smoothing, as well as the relationship between the quality of the stereoscopic scene and properties of the rendered images such as shape compactness.The experiment evaluated five reconstruction filters on four different volumetric datasets. Participants rated the stereoscopic scenes on four quality measures: depth quality, depth layout, lack of jaggyness, and sharpness. The results show that the correlation between the quality measures and post-aliasing and smoothing, which are properties associated with each reconstruction filter, is moderate and statistically insignificant. On the other hand, the correlation between the quality measures and compactness, which is a property specific to each rendered image, is strong and statistically significant.

[1]  David J. Hancock Distributed volume rendering and stereoscopic display for radiotherapy treatment planning , 2001 .

[2]  Richard L. Church,et al.  UC Office of the President Recent Work Title An efficient measure of compactness for two-dimensional shapes and its application in regionalization problems Permalink , 2013 .

[3]  William F. Reinhart Gray-scale requirements for antialiasing of stereoscopic graphic imagery , 1992, Electronic Imaging.

[4]  N NetravaliArun,et al.  Reconstruction filters in computer-graphics , 1988 .

[5]  Stéphane Ploix,et al.  A perceptive evaluation of volume rendering techniques , 2007, TAP.

[6]  Alexander Raake,et al.  Evaluating Depth Perception of 3D Stereoscopic Videos , 2012, IEEE Journal of Selected Topics in Signal Processing.

[7]  R. Keys Cubic convolution interpolation for digital image processing , 1981 .

[8]  D. Louis Collins,et al.  An Evaluation of Depth Enhancing Perceptual Cues for Vascular Volume Visualization in Neurosurgery , 2014, IEEE Transactions on Visualization and Computer Graphics.

[9]  Timo Ropinski,et al.  Visually Supporting Depth Perception in Angiography Imaging , 2006, Smart Graphics.

[10]  Jean-Bernard Martens,et al.  Quality asessment of coded images using numerical category scaling , 1995, Other Conferences.

[11]  Colin Ware,et al.  Evaluating stereo and motion cues for visualizing information nets in three dimensions , 1996, TOGS.

[12]  Balázs Csébfalvi,et al.  An Evaluation of Prefiltered Reconstruction Schemes for Volume Rendering , 2008, IEEE Transactions on Visualization and Computer Graphics.

[13]  R. Hamer,et al.  Effects of age and optical blur on real depth stereoacuity , 2010, Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians.

[14]  Andrea Giachetti,et al.  An interactive 3D medical visualization system based on a light field display , 2009, The Visual Computer.

[15]  Klaus Mueller,et al.  Classification and local error estimation of interpolation and derivative filters for volume rendering , 1996, Proceedings of 1996 Symposium on Volume Visualization.

[16]  Jonathan D. Pfautz,et al.  Depth Perception in Computer Graphics , 2000 .

[17]  H. Hauser,et al.  Mastering Windows: Improving Reconstruction , 2000, 2000 IEEE Symposium on Volume Visualization (VV 2000).

[18]  Arun N. Netravali,et al.  Reconstruction filters in computer-graphics , 1988, SIGGRAPH.

[19]  R. Osserman The isoperimetric inequality , 1978 .

[20]  Wijnand A. IJsselsteijn,et al.  Perceived quality of compressed stereoscopic images: Effects of symmetric and asymmetric JPEG coding and camera separation , 2006, TAP.

[21]  Sugato Chakravarty,et al.  Methodology for the subjective assessment of the quality of television pictures , 1995 .

[22]  IjsselsteijnWijnand,et al.  Perceived quality of compressed stereoscopic images , 2006 .

[23]  Steve Marschner,et al.  An evaluation of reconstruction filters for volume rendering , 1994, Proceedings Visualization '94.

[24]  Prabhat,et al.  A Comparative Study of Desktop, Fishtank, and Cave Systems for the Exploration of Volume Rendered Confocal Data Sets , 2008, IEEE Transactions on Visualization and Computer Graphics.

[25]  William Ribarsky,et al.  Stereo and motion cues effect on depth perception of volumetric data , 2014, Electronic Imaging.

[26]  Philip J. Corriveau,et al.  Psychovisual aspects of viewing stereoscopic video sequences , 1998, Electronic Imaging.

[27]  Thierry Blu,et al.  Linear interpolation revitalized , 2004, IEEE Transactions on Image Processing.

[28]  Ioannis Ivrissimtzis,et al.  An evaluation of reconstruction filters for a path-searching task in 3D , 2014, 2014 Sixth International Workshop on Quality of Multimedia Experience (QoMEX).

[29]  Hsieh Hou,et al.  Cubic splines for image interpolation and digital filtering , 1978 .

[30]  Doug A. Bowman,et al.  Validation of the MR Simulation Approach for Evaluating the Effects of Immersion on Visual Analysis of Volume Data , 2012, IEEE Transactions on Visualization and Computer Graphics.

[31]  Ingrid Carlbom,et al.  Optimal filter design for volume reconstruction and visualization , 1993, Proceedings Visualization '93.

[32]  Lars Kjelldahl,et al.  Effects of image resolution on depth perception in stereo and nonstereo images , 1997, Electronic Imaging.

[33]  Kwan-Liu Ma,et al.  Perceptually-Based Depth-Ordering Enhancement for Direct Volume Rendering , 2013, IEEE Transactions on Visualization and Computer Graphics.

[34]  Leonid I. Dimitrov,et al.  Enhanced Voxelization and Representation of Objects with Sharp Details in Truncated Distance Fields , 2010, IEEE Transactions on Visualization and Computer Graphics.

[35]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[36]  Doug A. Bowman,et al.  Effects of VR System Fidelity on Analyzing Isosurface Visualization of Volume Datasets , 2014, IEEE Transactions on Visualization and Computer Graphics.

[37]  Marta Kersten,et al.  STEREOSCOPIC VOLUME RENDERING OF MEDICAL IMAGES , 2005 .